A population-based urinary and plasma metabolomics study of environmental exposure to cadmium.

BACKGROUND: The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies. METHOD: We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure. RESULT: Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle). CONCLUSION: These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Optimal index for detecting splenic involvement on 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in diffuse large B-cell lymphoma.

Accurate clinical staging is important in diffuse large B-cell lymphoma (DLBCL) to adapt to optimal therapy. Splenic involvement of DLBCL has been recently more detectable with the advancement of a diagnostic scan by 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT). Our clinical question is whether splenic involvement was adequately diagnosed by FDG-PET/CT imaging. This retrospective study aimed to determine the optimal index for evaluating splenic involvement in patients with DLBCL. Patients with newly diagnosed DLBCL who were examined with FDG-PET/CT at diagnosis and the end of induction chemotherapy (EOI) was enrolled. The splenic involvement with the splenic FDG uptake value higher than that of the liver at diagnosis or with the decrease of splenic uptake at EOI by visual evaluation was evaluated as positive. The calculative evaluation of splenic involvement, based on the data of standardized uptake value (SUV) of the spleen, used maximum SUV (SUVmax), mean SUV (SUVmean), spleen total lesion glycolysis (spleen TLG), and spleen length. A change in each index following induction chemotherapy was expressed as an index. Receiver operating characteristic analysis was used to set the cutoff value for each index. This study included 52 patients. Spleen TLG (0.904) showed the best accuracy, followed by SUVmax (0.885) and SUVmean (0.885), among the 5 indexes for splenic involvement at diagnosis. Splenic involvement was predicted with a higher accuracy level (0.923) when selecting the cases with values higher than the cutoff level on both spleen TLG and SUVmax. The decision at EOI was more suitable by selecting both positive cases of ∆ TLG and ∆ SUVmax. Obtaining both the positive spleen TLG and SUVmax is recommended at diagnosis to predict splenic involvement. The assessment by ∆ spleen TLG and ∆ SUVmax seems to be optimal.

Association of Nonalcoholic Fatty Liver Disease with Arterial Stiffness and its Metabolomic Profiling in Japanese Community-Dwellers.

AIMS: Nonalcoholic fatty liver disease (NAFLD) is known to be associated with atherosclerosis. This study focused on upstream changes in the process by which NAFLD leads to atherosclerosis. The study aimed to confirm the association between NAFLD and the cardio-ankle vascular index (CAVI), an indicator of subclinical atherosclerosis, and explore metabolites involved in both by assessing 94 plasma polar metabolites. METHODS: A total of 928 Japanese community-dwellers (306 men and 622 women) were included in this study. The association between NAFLD and CAVI was examined using a multivariable regression model adjusted for confounders. Metabolites commonly associated with NAFLD and CAVI were investigated using linear mixed-effects models in which batch numbers of metabolite measurements were used as a random-effects variable, and false discovery rate-adjusted p-values were calculated. To determine the extent to which these metabolites mediated the association between NAFLD and CAVI, mediation analysis was conducted. RESULTS: NAFLD was positively associated with CAVI (coefficients [95% Confidence intervals (CI)]=0.23 [0.09-0.37]; p=0.001). A total of 10 metabolites were involved in NAFLD and CAVI, namely, branched-chain amino acids (BCAAs; valine, leucine, and isoleucine), aromatic amino acids (AAAs; tyrosine and tryptophan), alanine, proline, glutamic acid, glycerophosphorylcholine, and 4-methyl-2-oxopentanoate. Mediation analysis showed that BCAAs mediated more than 20% of the total effect in the association between NAFLD and CAVI. CONCLUSIONS: NAFLD was associated with a marker of atherosclerosis, and several metabolites related to insulin resistance, including BCAAs and AAAs, could be involved in the process by which NAFLD leads to atherosclerosis.

Genetic mutation in Escherichia coli genome during adaptation to the murine intestine is optimized for the host diet.

Mammalian gut microbes colonize the intestinal tract of their host and adapt to establish a microbial ecosystem. The host diet changes the nutrient profile of the intestine and has a high impact on microbiota composition. Genetic mutations in Escherichia coli, a prevalent species in the human gut, allow for adaptation to the mammalian intestine, as reported in previous studies. However, the extent of colonization fitness in the intestine elevated by genetic mutation and the effects of diet change on these mutations in E. coli are still poorly known. Here, we show that notable mutations in sugar metabolism-related genes (gatC, araC, and malI) were detected in the E. coli K-12 genome just 2 weeks after colonization in the germ-free mouse intestine. In addition to elevated fitness by deletion of gatC, as previously reported, deletion of araC and malI also elevated E. coli fitness in the murine intestine in a host diet-dependent manner. In vitro cultures of medium containing nutrients abundant in the intestine (e.g., galactose, N-acetylglucosamine, and asparagine) also showed increased E. coli fitness after deletion of the genes-of-interest associated with their metabolism. Furthermore, the host diet was found to influence the developmental trajectory of gene mutations in E. coli. Taken together, we suggest that genetic mutations in E. coli are selected in response to the intestinal environment, which facilitates efficient utilization of nutrients abundant in the intestine under laboratory conditions. Our study offers some insight into the possible adaptation mechanisms of gut microbes.IMPORTANCEThe gut microbiota is closely associated with human health and is greatly impacted by the host diet. Bacteria such as Escherichia coli live in the gut all throughout the life of a human host and adapt to the intestinal environment. Adaptive mutations in E. coli are reported to enhance fitness in the mammalian intestine, but to what extent is still poorly known. It is also unknown whether the host diet affects what genes are mutated and to what extent fitness is affected. This study suggests that genetic mutations in the E. coli K-12 strain are selected in response to the intestinal environment and facilitate efficient utilization of abundant nutrients in the germ-free mouse intestine. Our study provides a better understanding of these intestinal adaptation mechanisms of gut microbes.

Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS).

The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study used an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability, functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.

Reliability of Time-Series Plasma Metabolome Data over 6 Years in a Large-Scale Cohort Study.

Studies examining long-term longitudinal metabolomic data and their reliability in large-scale populations are limited. Therefore, we aimed to evaluate the reliability of repeated measurements of plasma metabolites in a prospective cohort setting and to explore intra-individual concentration changes at three time points over a 6-year period. The study participants included 2999 individuals (1317 men and 1682 women) from the Tsuruoka Metabolomics Cohort Study, who participated in all three surveys-at baseline, 3 years, and 6 years. In each survey, 94 plasma metabolites were quantified for each individual and quality control (QC) sample. The coefficients of variation of QC, intraclass correlation coefficients, and change rates of QC were calculated for each metabolite, and their reliability was classified into three categories: excellent, fair to good, and poor. Seventy-six percent (71/94) of metabolites were classified as fair to good or better. Of the 39 metabolites grouped as excellent, 29 (74%) in men and 26 (67%) in women showed significant intra-individual changes over 6 years. Overall, our study demonstrated a high degree of reliability for repeated metabolome measurements. Many highly reliable metabolites showed significant changes over the 6-year period, suggesting that repeated longitudinal metabolome measurements are useful for epidemiological studies.

Metabolomics profiles alterations in cigarette smokers and heated tobacco product users.

BACKGROUND: Heated tobacco products (HTPs) have gained global popularity, but their health risks remain unclear. Therefore, the current study aimed to identify plasma metabolites associated with smoking and HTP use in a large Japanese population to improve health risk assessment. METHODS: Metabolomics data from 9,922 baseline participants of the Tsuruoka Metabolomics Cohort Study (TMCS) were analyzed to determine the association between smoking habits and plasma metabolites. Moreover, alterations in smoking-related metabolites among HTP users were examined based on data obtained from 3,334 participants involved from April 2018 to June 2019 in a follow-up survey. RESULTS: Our study revealed that cigarette smokers had metabolomics profiles distinct from never smokers, with 22 polar metabolites identified as candidate biomarkers for smoking. These biomarker profiles of HTP users were closer to those of cigarette smokers than those of never smokers. The concentration of glutamate was higher in cigarette smokers, and biomarkers involved in glutamate metabolism were also associated with cigarette smoking and HTP use. Network pathway analysis showed that smoking was associated with the glutamate pathway, which could lead to endothelial dysfunction and atherosclerosis of the vessels. CONCLUSIONS: Our study showed that the glutamate pathway is affected by habitual smoking. These changes in the glutamate pathway may partly explain the mechanism by which cigarette smoking causes cardiovascular disease. HTP use was also associated with glutamate metabolism, indicating that HTP use may contribute to the development of cardiovascular disease through mechanisms similar to those in cigarette use.

Systematic Analysis of Diverse Polynucleotide Kinase Clp1 Family Proteins in Eukaryotes: Three Unique Clp1 Proteins of Trypanosoma brucei.

The Clp1 family proteins, consisting of the Clp1 and Nol9/Grc3 groups, have polynucleotide kinase (PNK) activity at the 5' end of RNA strands and are important enzymes in the processing of some precursor RNAs. However, it remains unclear how this enzyme family diversified in the eukaryotes. We performed a large-scale molecular evolutionary analysis of the full-length genomes of 358 eukaryotic species to classify the diverse Clp1 family proteins. The average number of Clp1 family proteins in eukaryotes was 2.3 ± 1.0, and most representative species had both Clp1 and Nol9/Grc3 proteins, suggesting that the Clp1 and Nol9/Grc3 groups were already formed in the eukaryotic ancestor by gene duplication. We also detected an average of 4.1 ± 0.4 Clp1 family proteins in members of the protist phylum Euglenozoa. For example, in Trypanosoma brucei, there are three genes of the Clp1 group and one gene of the Nol9/Grc3 group. In the Clp1 group proteins encoded by these three genes, the C-terminal domains have been replaced by unique characteristics domains, so we designated these proteins Tb-Clp1-t1, Tb-Clp1-t2, and Tb-Clp1-t3. Experimental validation showed that only Tb-Clp1-t2 has PNK activity against RNA strands. As in this example, N-terminal and C-terminal domain replacement also contributed to the diversification of the Clp1 family proteins in other eukaryotic species. Our analysis also revealed that the Clp1 family proteins in humans and plants diversified through isoforms created by alternative splicing.

Quality Control of Targeted Plasma Lipids in a Large-Scale Cohort Study Using Liquid Chromatography-Tandem Mass Spectrometry.

High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography-mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics.

Temporal phosphoproteomic analysis of VEGF-A signaling in HUVECs: an insight into early signaling events associated with angiogenesis.

Vascular endothelial growth factor-A (VEGF-A) is one of the primary factors promoting angiogenesis in endothelial cells. Although defects in VEGF-A signaling are linked to diverse pathophysiological conditions, the early phosphorylation-dependent signaling events pertinent to VEGF-A signaling remain poorly defined. Hence, a temporal quantitative phosphoproteomic analysis was performed in human umbilical vein endothelial cells (HUVECs) treated with VEGF-A-165 for 1, 5 and 10 min. This led to the identification and quantification of 1971 unique phosphopeptides corresponding to 961 phosphoproteins and 2771 phosphorylation sites in total. Specifically, 69, 153, and 133 phosphopeptides corresponding to 62, 125, and 110 phosphoproteins respectively, were temporally phosphorylated at 1, 5, and 10 min upon addition of VEGF-A. These phosphopeptides included 14 kinases, among others. This study also captured the phosphosignaling events directed through RAC, FAK, PI3K-AKT-MTOR, ERK, and P38 MAPK modules with reference to our previously assembled VEGF-A/VEGFR2 signaling pathway map in HUVECs. Apart from a significant enrichment of biological processes such as cytoskeleton organization and actin filament binding, our results also suggest a role of AAK1-AP2M1 in the regulation of VEGFR endocytosis. Taken together, the temporal quantitative phosphoproteomics analysis of VEGF signaling in HUVECs revealed early signaling events and we believe that this analysis will serve as a starting point for the analysis of differential signaling across VEGF members toward the full elucidation of their role in the angiogenesis processes. Workflow for the identification of early phosphorylation events induced by VEGF-A-165 in HUVEC cells.

iDMET: network-based approach for integrating differential analysis of cancer metabolomics.

BACKGROUND: Comprehensive metabolomic analyses have been conducted in various institutes and a large amount of metabolomic data are now publicly available. To help fully exploit such data and facilitate their interpretation, metabolomic data obtained from different facilities and different samples should be integrated and compared. However, large-scale integration of such data for biological discovery is challenging given that they are obtained from various types of sample at different facilities and by different measurement techniques, and the target metabolites and sensitivities to detect them also differ from study to study. RESULTS: We developed iDMET, a network-based approach to integrate metabolomic data from different studies based on the differential metabolomic profiles between two groups, instead of the metabolite profiles themselves. As an application, we collected cancer metabolomic data from 27 previously published studies and integrated them using iDMET. A pair of metabolomic changes observed in the same disease from two studies were successfully connected in the network, and a new association between two drugs that may have similar effects on the metabolic reactions was discovered. CONCLUSIONS: We believe that iDMET is an efficient tool for integrating heterogeneous metabolomic data and discovering novel relationships between biological phenomena.

1000 spider silkomes: Linking sequences to silk physical properties.

Spider silks are among the toughest known materials and thus provide models for renewable, biodegradable, and sustainable biopolymers. However, the entirety of their diversity still remains elusive, and silks that exceed the performance limits of industrial fibers are constantly being found. We obtained transcriptome assemblies from 1098 species of spiders to comprehensively catalog silk gene sequences and measured the mechanical, thermal, structural, and hydration properties of the dragline silks of 446 species. The combination of these silk protein genotype-phenotype data revealed essential contributions of multicomponent structures with major ampullate spidroin 1 to 3 paralogs in high-performance dragline silks and numerous amino acid motifs contributing to each of the measured properties. We hope that our global sampling, comprehensive testing, integrated analysis, and open data will provide a solid starting point for future biomaterial designs.

Identification of Attenuators of Transcriptional Termination: Implications for RNA Regulation in Escherichia coli.

The regulatory function of many bacterial small RNAs (sRNAs) requires the binding of the RNA chaperone Hfq to the 3' portion of the sRNA intrinsic terminator, and therefore sRNA signaling might be regulated by modulating its terminator. Here, using a multicopy screen developed with the terminator of sRNA SgrS, we identified an sRNA gene (cyaR) and three protein-coding genes (cspD, ygjH, and rof) that attenuate SgrS termination in Escherichia coli. Analyses of CyaR and YgjH, a putative tRNA binding protein, suggested that the CyaR activity was indirect and the effect of YgjH was moderate. Overproduction of the protein attenuators CspD and Rof resulted in more frequent readthrough at terminators of SgrS and two other sRNAs, and regulation by SgrS of target mRNAs was reduced. The effect of Rof, a known inhibitor of Rho, was mimicked by bicyclomycin or by a rho mutant, suggesting an unexpected role for Rho in sRNA termination. CspD, a member of the cold shock protein family, bound both terminated and readthrough transcripts, stabilizing them and attenuating termination. By RNA sequencing analysis of the CspD overexpression strain, we found global effects of CspD on gene expression across some termination sites. We further demonstrated effects of endogenous CspD under slow growth conditions where cspD is highly expressed. These findings provided evidence of changes in the efficiency of intrinsic termination, confirming this as an additional layer of the regulation of sRNA signaling. IMPORTANCE Growing evidence suggests that the modulation of intrinsic termination and readthrough of transcription is more widespread than previously appreciated. For small RNAs, proper termination plays a critical role in their regulatory function. Here, we present a multicopy screen approach to identify factors that attenuate small RNA termination and therefore abrogate signaling dependent on the small RNA. This study highlights a new aspect of regulation of small RNA signaling as well as the modulation of intrinsic termination.

Comparative Metabolomics of Small Molecules Specifically Expressed in the Dorsal or Ventral Marginal Zones in Vertebrate Gastrula.

Many previous studies have reported the various proteins specifically secreted as inducers in the dorsal or ventral regions in vertebrate gastrula. However, little is known about the effect on cell fate of small molecules below 1000 Da. We therefore tried to identify small molecules specifically expressed in the dorsal marginal zone (DMZ) or ventral marginal zone (VMZ) in vertebrate gastrula. Small intracellular and secreted molecules were detected using explants and supernatant samples. Hydrophilic metabolites were analyzed by capillary ion chromatography-mass spectrometry and liquid chromatography-mass spectrometry, and lipids were analyzed by supercritical fluid chromatography-tandem mass spectrometry. In total, 190 hydrophilic metabolites and 396 lipids were identified. The DMZ was found to have high amounts of glycolysis- and glutathione metabolism-related metabolites in explants, and the VMZ was richer in purine metabolism-related metabolites. We also discovered some hydrophilic metabolites and lipids differentially contained in the DMZ or VMZ. Our research would contribute to a deeper understanding of the cellular physiology that regulates early embryogenesis.

Features of smaller ribosomes in candidate phyla radiation (CPR) bacteria revealed with a molecular evolutionary analysis.

The candidate phyla radiation (CPR) is a large bacterial group consisting mainly of uncultured lineages. They have small cells and small genomes, and they often lack ribosomal proteins uL1, bL9, and/or uL30, which are basically ubiquitous in non-CPR bacteria. Here, we comprehensively analyzed the genomic information on CPR bacteria and identified their unique properties. The distribution of protein lengths in CPR bacteria peaks at around 100-150 amino acids, whereas the position of the peak varies in the range of 100-300 amino acids in free-living non-CPR bacteria, and at around 100-200 amino acids in most symbiotic non-CPR bacteria. These results show that the proteins of CPR bacteria are smaller, on average, than those of free-living non-CPR bacteria, like those of symbiotic non-CPR bacteria. We found that ribosomal proteins bL28, uL29, bL32, and bL33 have been lost in CPR bacteria in a taxonomic lineage-specific manner. Moreover, the sequences of approximately half of all ribosomal proteins of CPR differ, in part, from those of non-CPR bacteria, with missing regions or specifically added regions. We also found that several regions in the 16S, 23S, and 5S rRNAs of CPR bacteria are lacking, which presumably caused the total predicted lengths of the three rRNAs of CPR bacteria to be smaller than those of non-CPR bacteria. The regions missing in the CPR ribosomal proteins and rRNAs are located near the surface of the ribosome, and some are close to one another. These observations suggest that ribosomes are smaller in CPR bacteria than those in free-living non-CPR bacteria, with simplified surface structures.

Salivary metabolomics with machine learning for colorectal cancer detection.

As the worldwide prevalence of colorectal cancer (CRC) increases, it is vital to reduce its morbidity and mortality through early detection. Saliva-based tests are an ideal noninvasive tool for CRC detection. Here, we explored and validated salivary biomarkers to distinguish patients with CRC from those with adenoma (AD) and healthy controls (HC). Saliva samples were collected from patients with CRC, AD, and HC. Untargeted salivary hydrophilic metabolite profiling was conducted using capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry. An alternative decision tree (ADTree)-based machine learning (ML) method was used to assess the discrimination abilities of the quantified metabolites. A total of 2602 unstimulated saliva samples were collected from subjects with CRC (n = 235), AD (n = 50), and HC (n = 2317). Data were randomly divided into training (n = 1301) and validation datasets (n = 1301). The clustering analysis showed a clear consistency of aberrant metabolites between the two groups. The ADTree model was optimized through cross-validation (CV) using the training dataset, and the developed model was validated using the validation dataset. The model discriminating CRC + AD from HC showed area under the receiver-operating characteristic curves (AUC) of 0.860 (95% confidence interval [CI]: 0.828-0.891) for CV and 0.870 (95% CI: 0.837-0.903) for the validation dataset. The other model discriminating CRC from AD + HC showed an AUC of 0.879 (95% CI: 0.851-0.907) and 0.870 (95% CI: 0.838-0.902), respectively. Salivary metabolomics combined with ML demonstrated high accuracy and versatility in detecting CRC.

Time-series transcriptomic screening of factors contributing to the cross-tolerance to UV radiation and anhydrobiosis in tardigrades.

BACKGROUND: Tardigrades are microscopic animals that are capable of tolerating extreme environments by entering a desiccated state of suspended animation known as anhydrobiosis. While antioxidative stress proteins, antiapoptotic pathways and tardigrade-specific intrinsically disordered proteins have been implicated in the anhydrobiotic machinery, conservation of these mechanisms is not universal within the phylum Tardigrada, suggesting the existence of overlooked components. RESULTS: Here, we show that a novel Mn-dependent peroxidase is an important factor in tardigrade anhydrobiosis. Through time-series transcriptome analysis of Ramazzottius varieornatus specimens exposed to ultraviolet light and comparison with anhydrobiosis entry, we first identified several novel gene families without similarity to existing sequences that are induced rapidly after stress exposure. Among these, a single gene family with multiple orthologs that is highly conserved within the phylum Tardigrada and enhances oxidative stress tolerance when expressed in human cells was identified. Crystallographic study of this protein suggested Zn or Mn binding at the active site, and we further confirmed that this protein has Mn-dependent peroxidase activity in vitro. CONCLUSIONS: Our results demonstrated novel mechanisms for coping with oxidative stress that may be a fundamental mechanism of anhydrobiosis in tardigrades. Furthermore, localization of these sets of proteins mainly in the Golgi apparatus suggests an indispensable role of the Golgi stress response in desiccation tolerance.

Impact of Selected Initial Titration Schedules on Safety and Long-Term Effectiveness of Lamotrigine for the Treatment of Mood Disorders.

PURPOSE: Lamotrigine (LTG) is used for treatment of mood disorders, but it is associated with the risk of rash occurrence in the initial administration phase. Although slow titration reduces this risk, its effectiveness in the treatment of mood disorders has not been verified. The effects of titration method on the safety and effectiveness of LTG for the treatment of mood disorders were examined in this study. METHODS: This retrospective cohort study included 312 patients with mood disorders who underwent initiation of LTG therapy. Data regarding baseline demographics, titration schedules, concomitant medications, and time to and cause of discontinuation of LTG were collected. A multivariate analysis was used to evaluate the effects of the titration schedules. The 12-month effectiveness was also evaluated. RESULTS: The 12-month discontinuation rate of LTG was 16.7%. The most frequent cause of discontinuation was development of a rash (47.7%, n = 312). Fast titration (adjusted odds ratio, 8.15) significantly increased the risk of rash development, and slow titration (adjusted odds ratio, 0.29) significantly decreased this risk. The time to all-cause discontinuation was not significantly different between the slow and standard titration groups (n = 303). After 12 months of treatment, the condition of 46.7% patients were rated much or very much improved using CGI-C. CONCLUSIONS: Although slow titration of LTG reduces the occurrence of a rash, it is not more effective than standard titration in the long term. Optimizing the initial LTG titration schedule for patients with mood disorders is challenging.

Polarity protein SCRIB interacts with SLC3A2 to regulate proliferation and tamoxifen resistance in ER+ breast cancer.

Estrogen receptor (ER) positive breast cancer represents 75% of all breast cancers in women. Although patients with ER+ cancers receive endocrine therapies, more than 30% develop resistance and succumb to the disease, highlighting the need to understand endocrine resistance. Here we show an unexpected role for the cell polarity protein SCRIB as a tumor-promoter and a regulator of endocrine resistance in ER-positive breast cancer cells. SCRIB expression is induced by estrogen signaling in a MYC-dependent manner. SCRIB interacts with SLC3A2, a heteromeric component of leucine amino acid transporter SLC7A5. SLC3A2 binds to the N-terminus of SCRIB to facilitate the formation of SCRIB/SLC3A2/LLGL2/SLC7A5 quaternary complex required for membrane localization of the amino acid transporter complex. Both SCRIB and SLC3A2 are required for cell proliferation and tamoxifen resistance in ER+ cells identifying a new role for the SCRIB/SLC3A2 complex in ER+ breast cancer.

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study.

This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 pneumonia, and the healthy using chest X-ray (CXR) images. One private and two public datasets of CXR images were included. The private dataset included CXR from six hospitals. A total of 14,258 and 11,253 CXR images were included in the 2 public datasets and 455 in the private dataset. A deep learning model based on EfficientNet with noisy student was constructed using the three datasets. The test set of 150 CXR images in the private dataset were evaluated by the deep learning model and six radiologists. Three-category classification accuracy and class-wise area under the curve (AUC) for each of the COVID-19 pneumonia, non-COVID-19 pneumonia, and healthy were calculated. Consensus of the six radiologists was used for calculating class-wise AUC. The three-category classification accuracy of our model was 0.8667, and those of the six radiologists ranged from 0.5667 to 0.7733. For our model and the consensus of the six radiologists, the class-wise AUC of the healthy, non-COVID-19 pneumonia, and COVID-19 pneumonia were 0.9912, 0.9492, and 0.9752 and 0.9656, 0.8654, and 0.8740, respectively. Difference of the class-wise AUC between our model and the consensus of the six radiologists was statistically significant for COVID-19 pneumonia (p value = 0.001334). Thus, an accurate model of deep learning for the three-category classification could be constructed; the diagnostic performance of our model was significantly better than that of the consensus interpretation by the six radiologists for COVID-19 pneumonia.